NUMERICAL SIMULATION EXPERIMENTS BY NESTING HYDROLOGY MODEL DHSVM WITH REGIONAL CLIMATE MODEL RegCM2/CHINA

Based on improvement of a distributed hydrology-soil-vegetation model (DHSVM for short)and its application to North China,a nested regional climatic-hydrologic model system is developedby connecting DHSVM with RegCM2/China.The simulated climate scenarios,including controland 2×CO_2 outputs,are downscaled to 8 stations in Luanhe River and Sanggan River Basins todrive the hydrology model.According to simulation results,under double CO_2 scenarios,annualmean temperature and evapotranspiration will increase 2.8C and 29 mm,respectively;precipitation also increase but with different value for each basin,6 mm for Luanhe River Basinwhile 46 mm for Sanggan River Basin;runoff change for the two basins is different too,27 mmdecrease for Luanhe River Basin while 26 mm increase for Sanggan River Basin.As a result,therunoff in future for Luanhe River Basin and Sanggan River Basin will be 74 mm and 71 mm,respectively,which is approximately a quarter of annual mean runoff(284 mm)of the wholecountry.Total streamflow for the two basins will decrease about 2.5×10~8m~3.All these indicatethat the warm and dry trend will continue in the two river basins under double CO_2 scenarios.Thenested model system,with both climatic and hydrologic prediction ability,could also be applied toother basins in China by parameter adjustment.     

A fast and efficient integrity computation for non-precision approach performance assessment

The level of safety to be expected from global positioning system (GPS) must be known in order to use it to support safety critical operations such as air navigation. This is captured by the navigation performance parameter of integrity which includes the ability of the navigation system to deliver a warning to the user in the event of a significant failure and within a specified time-to-alert. Given the high percentile requirement associated with integrity, assessment of expected system performance both in the nominal case and during failure events, requires the application of analytical techniques. This paper identifies the weaknesses of the current methods for assessing the level of performance to be expected of GPS for non-precision approaches and proposes ways to address them including a novel application of a mathematical integration technique that greatly reduces the computational load associated with integrity performance calculations. Results based on computation times show that the new method reduces computational load by a factor of 500+ with a high accuracy and associated high level of confidence. It is shown that in some cases, the technique presented is able to improve GPS RAIM availability beyond the gains achieved by measurement weighting.     

Single epoch estimation of the Galileo integrity chain sensor station clock offsets

The Galileo integrity chain depends on a number of key factors, one of which is contamination of the signal-in-space errors with residual errors other than imperfect modelling of satellite orbits and clocks. A potential consequence of this is that the user protection limit is driven not by the errors associated with the imperfect orbit and clock modelling, but by the distortions induced by noise and bias in the integrity chain. These distortions increase the minimum bias the integrity chain can guarantee to detect, which is reflected in the user protection limit. A contributor to this distortion is the inaccuracy associated with the estimation of the offset between the Galileo sensor station (GSS) receiver clocks and the Galileo system time (GST). This offset is termed the receiver clock synchronization error (CSE). This paper describes the research carried out to determine both the CSE and its associated error using GPS data as captured with the Galileo System Test Bed Version 1 (GSTB-V1). In the study we simulate open access to a time datum using IGS data. Two methods are compared for determining CSE and the corresponding uncertainty (noise) across a global network of tracking stations. The single-epoch single-station method is an ‘averaging’ technique that uses a single epoch of data, and is carried out at individual sensor stations, without recourse to the data from other stations. The global network solution method is also single epoch based, but uses the inversion of a linearised model of the global system to solve for the CSE simultaneously at all GSS along with a number of other parameters that would otherwise be absorbed into the CSE estimate in the averaging technique. To test the effectiveness of various configurations in the two methods the estimated synchronisation errors across the GSS network (comprising 25 stations) are compared to the same values as estimated by the International GPS Service (IGS) using a global tracking network of around 150 stations, as well as precise orbit and satellite clock models determined by a combination of global analysis centres. The results show that the averaging technique is vulnerable to unmodelled errors in the satellite clock offsets from system time, leading to receiver CSE errors in the region of 12 ns (3.7 m), this value being largely driven by the satellite CSE errors. The global network approach is capable of delivering CSE errors at the level of 1.5 ns (46 cm) depending on the number of parameters in the linearised model. The International GNSS Service (IGS) receiver clock estimates were used as a truth model for comparative assessment.     

Integrity of an integrated GPS/INS system in the presence of slowly growing errors. Part I: A critical review

This paper (the first part of two to be published in this journal) presents the process and results of a critical review of the integrated GPS and inertial navigation system (INS) architectures, the corresponding failure modes and the existing integrity monitoring methods. The paper concludes that tightly coupled GPS/INS systems have the highest potential for detecting slowly growing errors (SGEs). This is due to access to pseudorange measurements and a relatively simpler configuration compared to the other architectures. The second paper (Part II) takes this further and carries out a detailed characterisation of the performance of the current integrity algorithms for tightly coupled systems and develops a new algorithm that detects SGEs faster than the current methods.     

A TEST OF THREE FITTING CRITERIA FOR MULTIRESPONSE NON-LINEAR MODELING

This work evaluates objective functions for multiresponse non-linear modeling using computersimulations.Tests are performed under a variety of signal-to-noise ratios and noise variance-covariancestructures.The standard error of prediction for the model parameters,computed from 50 trials,is usedfor performance comparisons.The full rank and rank-deficient problems are considered.For the fullrank problem one model was investigated,a first-order two-step consecutive reaction model,and twoobjective functions were considered,the total sum of squares and the determinant criterion.Nodistinction could be made between the two objective functions for this model.For the rank-deficient case two models were investigated,a first-order two-step consecutive reactionas in the full rank case,and a pH titration model described by the Henderson-Hasselbalch equation.Three objective functions were investigated for the rank-deficient case,the total sum of squares,aweighted total sum of squares and the determinant criterion.The total sum of squares was found toperform poorly under all conditions tested compared to the weighted total sum of squares and thedeterminant criterion.The determinant criterion was found to perform much better than the other twocriteria when the data have a combination of a low signal-to-noise ratio and high variance-covariancenoise structure.     

RECENT DEVELOPMENTS IN MULTIVARIATE CALIBRATION

With the goal of understanding global chemical processes,environmental chemists have some of the mostcomplex sample analysis problems.Multivariate calibration is a tool that can be applied successfully inmany situations where traditional univariate analyses cannot.The purpose of this paper is to reviewmultivariate calibration,with an emphasis being placed on the developments in recent years.The inverseand classical models are discussed briefly,with the main emphasis on the biased calibration methods.Principal component regression(PCR)and partial least squares(PLS)are discussed,along with methodsfor quantitative and qualitative validation of the calibration models.Non-linear PCR,non-linear PLSand locally weighted regression are presented as calibration methods for non-linear data.Finally,calibration techniques using a matrix of data per sample(second-order calibration)are discussed briefly.     

What determines perceived value of seasonal climate forecasts? A theoretical analysis

Seasonal forecasts have potential value as tools for the management of risks due to inter-annual climate variability and iterative adaptation to climate change. Despite their potential, forecasts are not widely used, in part due to poor performance and lack of relevance to specific users’ decision problems, and in part due to a variety of economic and behavioural factors. In this paper a theoretical model of perceived forecast value is proposed and applied to a stylized portfolio-type decision problem with wide applicability to actual forecast users, with a view to obtaining a more complete picture of the determinants of perceived value. The effects of user wealth, risk aversion, and perceived forecast trustworthiness, and presentational parameters, such as the position of forecast parameter categories, and the size of probability categories, on perceived value is investigated. Analysis of the model provides several strong qualitative predictions of how perceived forecast value depends on these factors. These predictions may be used to generate empirical hypotheses which offer the chance of evaluating the model's assumptions, and suggest several means of improving understanding of perceived value based on qualitative features of the results.     

Integrity monitoring of fixed ambiguity Precise Point Positioning (PPP) solutions

Traditional positioning methods, such as conventional Real Time Kinematic (cRTK) rely upon local reference networks to enable users to achieve high-accuracy positioning. The need for such relatively dense networks has significant cost implications. Precise Point Positioning (PPP) on the other hand is a positioning method capable of centimeter-level positioning without the need for such local networks, hence providing significant cost benefits especially in remote areas. This paper presents the state-of-the-art PPP method using both GPS and GLONASS measurements to estimate the float position solution before attempting to resolve GPS integer ambiguities. Integrity monitoring is carried out using the Imperial College Carrier-phase Receiver Autonomous Integrity Monitoring method. A new method to detect and exclude GPS base-satellite failures is developed. A base-satellite is a satellite whose measurements are differenced from other satellite’s measurements when using between-satellite-differenced measurements to estimate position. The failure detection and exclusion methods are tested using static GNSS data recorded by International GNSS Service stations both in static and dynamic processing modes. The results show that failure detection can be achieved in all cases tested and failure exclusion can be achieved for static cases. In the kinematic processing cases, failure exclusion is more difficult because the higher noise in the measurement residuals increases the difficulty to distinguish between failures associated with the base-satellite and other satellites.     

Economic risk assessment of Cotopaxi volcano,Ecuador, in case of a future lahar emplacement

Natural Hazards - The Cotopaxi volcano in north-central Ecuador is one of the most dangerous volcanoes of the world due to its ability to generate far-reaching lahars, which are able to destroy...     

Interannual variations and future change of wintertime extratropical cyclone activity over North America in CCSM3

Climatology and interannual variations of wintertime extratropical cyclone frequency in CCSM3 twentieth century simulation are compared with the NCEP/NCAR reanalysis during 1950–1999. CCSM3 can simulate the storm tracks reasonably well, although the model produces slightly less cyclones at the beginning of the Pacific and Atlantic storm tracks and weaker poleward deflection over the Pacific. As in the reanalysis, frequency of cyclones stronger than 980 hPa shows significant correlation with the Pacific/North America (PNA) teleconnection pattern over the Pacific region and with the North Atlantic Oscillation (NAO) in the Atlantic sector. Composite maps are constructed for opposite phases of El Nino-Southern Oscillation (ENSO) and the NAO and all anomalous patterns coincide with observed. One CCSM3 twenty-first century A1B scenario realization indicates there is significant increase in the extratropical cyclone frequency on the US west coast and decrease in Alaska. Meanwhile, cyclone frequency increases from the Great Lakes region to Quebec and decreases over the US east coast, suggesting a possible northward shift of the Atlantic storm tracks under the warmer climate. The cyclone frequency anomalies are closely linked to changes in seasonal mean states of the upper-troposphere zonal wind and baroclinicity in the lower troposphere. Due to lack of 6-hourly outputs, we cannot apply the cyclone-tracking algorithm to the other eight CCSM3 realizations. Based on the linkage between the mean state change and the cyclone frequency anomalies, it is likely a common feature among the other ensemble members that cyclone activity is reduced on the East Coast and in Alaska as a result of global warming.